I'm Managing Partner at gPress, a marketing, publishing, research and education consultancy. Previously, I held senior marketing and research management positions at NORC, DEC and EMC. Most recently, I was Senior Director, Thought Leadership Marketing at EMC, where I launched the Big Data conversation with the “How Much Information?” study (2000 with UC Berkeley) and the Digital Universe study (2007 with IDC). I blog at http://whatsthebigdata.com/ and http://infostory.com/ Twitter: @GilPress

Lots of organizations right now are saying, according to Ross, “Why don’t we do something cool with analytics?” But, to paraphrase a great philosopher, if they don’t know where they are going, it doesn’t matter which road they are taking. This is why they need data dictators, to force common data definitions across the business, to dictate “this is how we will define sales, this is how we will define returns, this is when we will register revenue, and we are all living by this rule.”

Years ago, John F. Rockart, another researcher affiliated with CISR, popularized “critical success factors” as a tool for helping CEOs fight data overload. He reported the frustration of a number of senior executives in a 1979 Harvard Business Review article:

“Why do I have to have dozens of reports a month and yet very little of the real information I need to manage this company?”

“The information explosion crosses and criss-crosses executive desks with a great deal of data. Much of this is only partly digested and much of it is irrelevant…”

“I think the problem with management information systems in the past in many companies has been that they’re overwhelming as far as the executive is concerned. He has to go through reams of reports and try to determine for himself what are the most critical pieces of information contained in the reports so that he can take the necessary action and correct any problems that have arisen.”

There is no doubt that in the past thirty years, progress has been made in helping senior executives get the most relevant data they need for managing their company. But what progress has been made in ensuring the quality of the data provided? Ross tells the story of Aetna in 2002 when its president, Ron Williams, tried to find out why the company lost $270 million in the previous year, only to discover that every single line of business presented data showing they were making a profit. Williams’ solution: “I was going to dictate every piece of data, and you are going to use my definition of data.” Says Ross: “This is what I think the great leaders get right: they dictate a single source of truth.”

Yes, that phrase again, the single source of truth. In the age of big data, with so much more data and so many new data sources, it’s imperative to determine what data to focus on and how to define it and how to ensure everybody in the organization (not just at the top) looks at the same version of a clean, updated data set. That’s what Ross calls (following Charlie Feld) sacred data:

“If your core data is bad, you can do analytics around the edges, but you’re never going to figure out how to avoid stock-outs or better serve customers. You’re not going to figure it out because you don’t have the data. There is just some data that, as messy as the process is, you’ve got to get right, and if you don’t give that data all the attention it needs, you’re not going to get there.”

Or as Ross wrote in a lively e-chat on AllAnalytics: “I think applying analytics to unstructured data is pointless if we don’t understand strategic priorities.”

But what defines the strategic priorities that define sacred data?

The editor in chief of the Harvard Business Review, Adi Ignatius, reminds us this month of the words of Wallace B. Donham, the second dean of Harvard Business School, in the first issue of HBR (1922), defining its mission as teaching managers “how a proper theory of business is to be obtained.”

If I may quote myself from a 1995 letter I wrote to Harvard Business Review editors in reaction to a Peter Drucker article titled “The Theory of the Business:”

“In both business and science, theories help us reduce the uncertainty of the world we live in. Theories also help us make sense of data, and they provide us with lenses to view and interpret the world. Without a theory, we cannot understand the causes of business success or failure. The theory of the business answers two fundamental questions of human motivation: Why do customers buy a company’s products and services? And why are the employees loyal to and enthusiastic about working for a company? It is a framework that provides employees with a meaning for their work and customers with compelling reasons to buy. In that sense, the theory of the business may not just explain reality, or past business success; it may also define it by communicating and convincing employees and customers that the company is unique.”

Data dictators should start by articulating the theory of their business. Martin Gardner, in The Annotated Alice, points out that the Cheshire Cat’s remarks are echoed in Jack Kerouac’s On the Road:

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